Video fingerprinting is sometimes used to generate a unique identifier for a video based on characteristics of the video's content. The resulting identifier can be used in video searching applications to locate a video based on its unique identifier, to match duplicate or near-duplicate copies of a given video, to identify unauthorized usage or ownership of copyrighted video material, or other such applications. To ensure reliable video matching, the video fingerprinting process should be designed to yield identifiers that are stable and invariant to video transformations such as cropping, scaling, image flipping, changes in perspective, or the like.
Some video fingerprinting processes generate unique identifiers by quantizing characteristics of the video's content. However, if the video's characteristics have been altered (e.g., by the aforementioned video transformations), the identifier generated for the altered video may not match the identifier generated for the original video. Local features having dimension values that reside near quantization grid boundaries are particularly susceptible to such video transformations, since relatively small changes may cause those values to quantize to a different integer value. Consequently, the resulting identifier has a higher likelihood of mismatching.
The above-described is merely intended to provide an overview of some of the challenges facing conventional systems. Other challenges with conventional systems and contrasting benefits of the various non-limiting embodiments described herein may become further apparent upon review of the following description.